1. Field of the Invention
The present invention relates to a data processing method used in the field of spectroscopy and capable of providing improved signal-to-noise ratio (S/N). The invention also relates to a spectrometer and a measuring apparatus operating based on the data processing method.
2. Description of Related Art
A nuclear magnetic resonance (NMR) spectrometer is now described as one example of spectrometer. The NMR spectrometer is an apparatus for analyzing the molecular structure of a sample placed within a static magnetic field by irradiating the sample with pulsed RF waves having the NMR frequency of the nuclei to be observed, then detecting a feeble RF signal (NMR) signal emanating from the sample, and extracting molecular structure information contained in the detected signal.
FIG. 1 is a schematic block diagram of an NMR spectrometer. This instrument includes an RF pulse generator 1 that generates RF pulses having the NMR resonance frequency of nuclei under observation. The generated RF pulses are so controlled as to have a specified RF phase φ, a specified pulse width, and a specified amplitude value. The RF pulses are fed to an NMR probe 4 via an RF amplifier 2 and a duplexer 3. Then, the RF pulses are applied to a sample under investigation from an irradiation/detection coil (not shown) placed within the probe 4.
After the RF pulse irradiation, a feeble NMR signal (free induction decay (FID) signal) produced from the sample is detected by the irradiation/detection coil and then fed via the duplexer 3 to a preamplifier 5, where the signal is amplified. Then, the signal is furnished to a receiver 6.
An FID signal in the audio-frequency range is obtained by demodulation performed in the receiver 6 and converted into a digital signal by an analog-to-digital converter 7. The digital signal is then fed to a control computer 8.
The control computer 8 supplies control signals to the RF pulse generator 1 to specify the RF phase φ, pulse width, and amplitude value. The computer 8 also Fourier transforms the FID signal accepted in the time domain into NMR spectral data in the frequency domain and displays the data as an NMR spectrum. If necessary, the computer makes a phase correction of the NMR spectrum. In practice, real-part and imaginary-part spectra are obtained as the NMR spectrum. Usually, the real-part spectrum is displayed as an NMR spectrum.
In such an NMR instrument, the sensitivity for NMR signals are expressed by the ratio of signal to noise, abbreviated as S/N. Heretofore, various approaches have been used to improve the S/N. The approaches can be classified into a technique for suppressing noise, a technique for increasing the signal intensity, and a technique for discriminating noise and signal from each other. A well-known technique most relevant to the present invention is the technique for discriminating noise and signal from each other.
The most widely accepted method of the techniques classified as the approach for discriminating noise and signal from each other is known as accumulation. That is, plural NMR signals are observed and summed up to thereby increase the signal intensity relative to noise. Consequently, the signal is enhanced, and a high-sensitivity NMR spectrum is obtained.
The key concept of this technique is that when plural measurements are made and the obtained signals are summed up, the signal increases in proportion to the number of measurements, while the noise increases in proportion to ½ power of the number of measurements. For example, if two measurements are made and the resulting signals are summed up, the signal is directly doubled. In contrast, the noise increases by a factor of 21/2 (about 1.4). When two measurements are made in this way, the signal is augmented relative to the noise. The sensitivity for NMR spectra, i.e., S/N, is increased by a factor of about 1.4.
Generally, if n accumulation steps are performed, the S/N is improved by a factor of n1/2. It is very easy to perform an accumulation operation and thus accumulation has been used for many years as a technique for improving the S/N. Furthermore, accumulation is a simple additive operation and, therefore, it is easy to realize it by a hardware configuration. Also, it is not necessary to increase the capacity of a memory used to hold measurement results. In this way, accumulation is an intuitive technique which is easy to implement and which covers a wide range of applications. Today, accumulation is a technique routinely used in spectrometers such as FT-IR, as well as in NMR. Where S/N is not sufficiently high, accumulation is an approach employed almost always. (See “C13 NMR, Fundamentals and Applications (in Japanese)”, written by Yoshito Takeuchi and Hidehiro Ishizuka, supervised by Shizuo Fujiwara, edited by Kodansha Scientific, published on Nov. 1, 1976, by Kodansha Ltd., pp. 145-148.)
Accumulation is a technique that is quite easy to use but it is said that there is the problem that the signal-to-noise ratio is not improved much when compared with the time taken for measurements. For example, if 16 accumulation steps are performed, the signal-to-noise ratio is improved by a factor of 161/2=4. That is, the signal-to-noise ratio is improved only by a factor of 4 though the measurement time is prolonged as long as 16 fold. If an accumulation operation is performed over the whole one day (24 hours) to improve the sensitivity, the sensitivity improvement is as small as four times compared with an accumulation operation performed for 1.5 hours.
In this way, where accumulation is applied, there is the problem that a very long measurement time is required to improve the signal-to-noise ratio and that the rate of improvement is not very good. We have considered that this problem arises from the fact that only the difference between the manner in which signal increases by a factor of n and the manner in which noise increases by a factor of n1/2, where n is the number of accumulation steps, is noticed in the accumulation technique in discriminating signal and noise.
More specifically, when the same measurement is repeated, the signal always produces the same result. On the other hand, noise produces random values. This feature has not been noticed sufficiently. When accumulation steps are performed, signal and noise behave differently. We have thought that if this is utilized, it is possible to develop a more effective method of discriminating signal and noise from each other.